Selected article for: "early stage and risk prediction"
Author: Lijiao Zeng; Jialu Li; Mingfeng Liao; Rui Hua; Pilai Huang; Mingxia Zhang; Youlong Zhang; Qinlang Shi; Zhaohua Xia; Xinzhong Ning; Dandan Liu; Jiu Mo; Ziyuan Zhou; Zigang Li; Yu Fu; Yuhui Liao; Jing Yuan; Lifei Wang; Qing He; Lei Liu; Kun Qiao
Title: Risk assessment of progression to severe conditions for patients with COVID-19 pneumonia: a single-center retrospective study
  • Document date: 2020_3_30
    • ID: 8n3q30hy_1
    Snippet: Since its first report in Wuhan, China, in December 2019, the SARS-CoV-2's outbreak has quickly became a global public health issue, with a total of 168,019 infected, 6,610 deaths and 148 countries affected as of Mar 16, 2020 (World Health Organization, WHO 1 ). One of main challenges facing its medical care is the lack of effective tools for selecting patients posing a high risk of mortality at an early stage. Previous studies have explored risk.....
    Document: Since its first report in Wuhan, China, in December 2019, the SARS-CoV-2's outbreak has quickly became a global public health issue, with a total of 168,019 infected, 6,610 deaths and 148 countries affected as of Mar 16, 2020 (World Health Organization, WHO 1 ). One of main challenges facing its medical care is the lack of effective tools for selecting patients posing a high risk of mortality at an early stage. Previous studies have explored risk factors associated with severity levels of the pneumonia. For example, Zhou et.al 2 identified that the older age and a high level of D-dimer are associated with in-hospital death, while Shi et.al 3 found that the manifestation of chest CT imaging abnormalities correlates with disease states. However, the joint analysis of time and progression event, as well as the integration of multiple types of input data into risk prediction, have not been thoroughly investigated.

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